Economic Contribution of Ohio’s Wood Industry Cluster: Identifying Opportunities in the Appalachian Region

Abstract

Ohio's wood industry cluster contributes nearly $25 billion and 116,321 jobs to the state's economy, yet most of this value-added impact occurs outside of the heavily forested Appalachian Ohio region. This research, conducted as part of a Small Business Administration Regional Innovation Cluster grant, includes a multi-industry economic contribution analysis to document wood industry impacts to the entire State of Ohio and the 32-county Appalachian Ohio region. Findings indicated that Appalachian Ohio contained lower paying and lower on the value chain sectors compared to the state. This paper highlights these metrics and presents recommendations to improve investment and value-added industry opportunities in the wood industry cluster to support Appalachian Ohio.

Industry survey of wood waste markets in Ohio

“…It is of note that the vast majority of wood waste in the state is produced in Appalachian Ohio (the southeast portion of the state), while the majority of our respondents come from outside of this region. This reflects the findings of other studies that show how Appalachia claims a lower place in the wood industry's value chain, primarily constituting the parts of the industry that produce the most wood waste but generate average wages of $5000 less than the wood industry in the rest of the state Michaud and Jolley 2019).…”

“…Prior research has noted the possibility for further growth, particularly in the Appalachian part of the state. Further, the effects of development in the wood industry are not limited to itself, as every job created in the wood industry generates 1.2 additional jobs in the state via the multiplier effect (Michaud et al 2017). Thus, a contribution to the wood industry is a contribution to the broader economy of Ohio.…”

“…The same study found that pulp and paper mills directly employ over 385,000 people and generate $149 billion in value added across the country (Jolley et al 2020). In the State of Ohio alone, the wood industry contributes $25 billion in economic output and employs 116,321 people (Michaud and Jolley 2019). One byproduct of this sizeable wood industry is the generation of wood waste, which began to receive considerable attention in the 1990s (Falk 1997), and continues to this day.…”

Using input–output models to estimate sectoral effects of carbon tax policy: Applications of the NGFS scenarios

“…In the United States context, IO modeling is often associated with IMPLAN, a proprietary software commonly used by researchers to estimate the economic impact of an exogenous change in the economy. Given IMPLAN's origination out of the US Forest Service in the 1970s (IMPLAN, 2022), it has been commonly used to estimate forestry‐related economic impacts at the national (e.g., Jolley et al, 2020; Pelkki & Sherman, 2020), regional (e.g., Aruna et al, 1997; Henderson et al, 2017; Joshi et al, 2017; Tilley & Munn, 2007), and state levels (e.g., LaBissoniere & Bowe, 2006; Lester et al, 2015; Michaud & Jolley, 2019). Despite its origin in the forestry sector, IMPLAN has expanded the use of IO modeling to examine the economic impact of economic shocks in a variety of economic sectors such as income changes (Jolley, 2022; Leatherman & Marcouiller, 1996; Paynter et al, 2014), colleges and universities (Jolley & Belleville Jr, 2021; Khalaf et al, 2022), and energy‐related projects (Bae & Dall'erba, 2016; Jolley et al, 2019; Khalaf, 2022; Michaud, 2018).…”

Basic income: a 50-state economic impact analysis

“…IMPLAN originated out of the United States Forest Service in the 1970s (IMPLAN, 2022) and has a long history of being used by academics and practitioners to examine the economic impact of changes in forest management and related economics (Jolley et al , 2020; Hodges and Rahmani, 2019; Michaud and Jolley, 2019; Dahal et al , 2017, among others). More recently, IMPLAN has been used by scholars to examine the economic impact of various energy production scenarios in areas such as shale gas production (Michaud, 2018), coal-fired power plants (Bowen and Deskins, 2021; Jolley et al , 2019), biomass and biofuels (Perez-Verdin et al , 2008; Lester et al , 2015) and wind and solar (Smith et al , 2018).…”